Bayesian inference of spatial and temporal relations in AI patents for EU countries.

In the paper, we propose two models of Artificial Intelligence (AI) patents in European Union (EU) countries addressing spatial and temporal behaviour. In particular, the models can quantitatively describe the interaction between countries or explain the rapidly growing trends in AI patents. For spatial analysis Poisson regression is used to explain collaboration between a pair of countries measured by the number of common patents. Through Bayesian inference, we estimated the strengths of interactions between countries in the EU and the rest of the world. In particular, a significant lack of cooperation has been identified for some pairs of countries. Alternatively, an inhomogeneous Poisson process combined with the logistic curve growth accurately models the temporal behaviour by an accurate trend line. Bayesian analysis in the time domain revealed an upcoming slowdown in patenting intensity.

Allele-dose association of the C5orf30 rs26232 variant with joint damage in rheumatoid arthritis.

OBJECTIVE: There is increasing evidence to indicate that genetic factors contribute significantly to radiologic joint damage in rheumatoid arthritis (RA). The aim of the present study was to determine whether genotypes of 10 recently identified RA susceptibility loci are associated with radiologic severity. METHODS: A 2-stage study was performed using 3 Northern European RA populations: a British cross-sectional population (discovery cohort; n=885) and the Leiden Early Arthritis Clinic (EAC) cohort (n=581) and Yorkshire Early Arthritis Register (YEAR) cohort (n=418) (validation cohorts). Radiologic damage was assessed using a modified Larsen method for scoring radiographs (in the discovery cohort) or modified Sharp/van der Heijde score (in the 2 validation cohorts). A meta-analysis was performed to bring together the evidence from the 3 studies, using data on radiologic severity of joint damage from a single time point. RESULTS: An allele-dose association of rs26232 was present in the discovery population (P=4×10(-4)); the median modified Larsen scores of radiologic joint damage per genotype were 31 (for those with CC), 27 (for those with CT), and 16 (for those with TT). The allele-dose association of rs26232 was replicated in both the Leiden EAC cohort during the initial 7 years of RA (P=0.04) and the YEAR cohort (P=0.039). In a fixed-effects meta-analysis of all 3 studies, the per T allele effect on the ratio of radiologic severity scores was 0.90 (95% confidence interval 0.84, 0.96; P=0.004). CONCLUSION: The variant rs26232, in the first intron of the C5orf30 locus, is associated with the severity of radiologic damage in RA and is independent of established prognostic biomarkers. The biologic activities of C5orf30 are unknown, but our genetic data suggest that it is involved in mediating joint damage in RA.

Mobile sailing robot for automatic estimation of fish density and monitoring water quality.

INTRODUCTION: The paper presents the methodology and the algorithm developed to analyze sonar images focused on fish detection in small water bodies and measurement of their parameters: volume, depth and the GPS location. The final results are stored in a table and can be exported to any numerical environment for further analysis. MATERIAL AND METHOD: The measurement method for estimating the number of fish using the automatic robot is based on a sequential calculation of the number of occurrences of fish on the set trajectory. The data analysis from the sonar concerned automatic recognition of fish using the methods of image analysis and processing. RESULTS: Image analysis algorithm, a mobile robot together with its control in the 2.4 GHz band and full cryptographic communication with the data archiving station was developed as part of this study. For the three model fish ponds where verification of fish catches was carried out (548, 171 and 226 individuals), the measurement error for the described method was not exceeded 8%. SUMMARY: Created robot together with the developed software has features for remote work also in the variety of harsh weather and environmental conditions, is fully automated and can be remotely controlled using Internet. Designed system enables fish spatial location (GPS coordinates and the depth). The purpose of the robot is a non-invasive measurement of the number of fish in water reservoirs and a measurement of the quality of drinking water consumed by humans, especially in situations where local sources of pollution could have a significant impact on the quality of water collected for water treatment for people and when getting to these places is difficult. The systematically used robot equipped with the appropriate sensors, can be part of early warning system against the pollution of water used by humans (drinking water, natural swimming pools) which can be dangerous for their health.